Online adaptive flux control for space vector PWM-DTC IM drives towards optimum efficiency design

An improved Direct Torque Controlled (DTC) Induction Motor (IM) is reported in this paper with the aims to produce an adaptive flux controller design to realize the maximum efficiency in DTC IM drives. The value of reference flux is identified through the artificial intelligent neural network (ANN) algorithm with the input power as the objective function. The description of neural network control system as well as the training procedure is explained in this paper. Consequently, the proposed efficient optimizing controller yields an adaptive reference flux, which ensures a minimum input power that leading to the maximum efficiency of the drives systems is achieved. The proposed schemes have been developed and the performance of the IM Drive under different operating condition has been investigated through simulation and experimentally by using the Simulink/Matlab and digital signal processor of dSPACE. The promising results validate the effectiveness.

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